News | Artificial Intelligence | April 01, 2019

Future of AI in Radiology Discussed in Chicago Breakfast Briefing

Paul J. Chang, M.D., will speak about AI's potential impact on medical imaging during an AIMed breakfast briefing at the University of Chicago School April 9.

Paul J. Chang, M.D., will speak about AI's potential impact on medical imaging during an AIMed breakfast briefing at the University of Chicago School April 9.

Paul J. Chang, M.D., FSIIM, professor and vice-chairman of radiology informatics at the University of Chicago School of Medicine will explain how artificial intelligence (AI) will improve the field of radiology and patient outcomes. This is part of a series of regional AI breakfast briefings hosted by AIMed, a collaborative group that is working to bring various subspecialties together to expand the use of AI to improve medicine.

The event is Tuesday, April 9, 2019, from 8-10 a.m. CDT, at the Gleacher Center, The University of Chicago Booth School of Business Room 300, Lounge 350, located at 450 Cityfront Plaza Dr. in Chicago.

Register for this event:
https://www.eventbrite.co.uk/e/experience-the-future-of-ai-in-radiology-chicago-tickets-56287456297

Creating a collaborative ecosystem and robust infrastructure is important to enable AI to improve the field of radiology and patient outcomes.
Artificial Intelligence has the power to truly transform radiological practice. The benefits of machine learning and deep neural networks in identifying disease earlier and more accurately is irrefutable. The integration of this technology at scale is, however, more challenging. How do we invest in building the necessary frameworks to validate these tools in the clinical setting? How do we ensure we are working in unison as an industry and not in a siloed and duplicative fashion. How do we ensure we maintain physician oversight/domain expertise when these tools are being developed?

Topics to be discussed will include
   · The need for unbiased Ground Truth Data
   · Overhaul of IT infrastructure within the healthcare system at large.
   · Patient privacy/protection issues
   · Develop comprehensive partnerships between clinicians with the vendor community to develop tools of clinical utility and usability
   · How do we speed up research without putting scientific integrity at risk. Is there a hybrid model?
 
Format:
8:00 – 08:30 Arrival, coffee and networking

8:30 – 08:40 Welcome and introduction by Freddy White, CEO AIMed

8:40 – 09:30 Panel discussion 9:30 – 09:50 General Q&A

9:50 – 09:55 Summary and close

9:55 – 10:15 Networking and coffee 

Breakfast pastries, coffee and various refreshmentswill be available.

Related Content

M*Modal and Community Health Network Partner on AI-powered Clinical Documentation
News | PACS Accessories | June 13, 2019
M*Modal announced that the company and Community Health Network (CHNw) are collaborating to transform the patient-...
iCAD Introduces ProFound AI for 2D Mammography in Europe
News | Artificial Intelligence | June 13, 2019
iCAD Inc. announced the launch of ProFound AI for 2D Mammography in Europe. This software is the latest addition to...
The Current Direction of Healthcare Reform Explained by CMS Administrator Seema Verma
News | Radiology Business | June 11, 2019
June 11, 2019 — Centers for Medicare and Medicaid Services (CMS) Administrator Seema Verma addressed the American Med
Aidoc Earns FDA Approval for AI for C-spine Fractures
Technology | Artificial Intelligence | June 11, 2019
Radiology artificial intelligence (AI) provider Aidoc announced the U.S. Food and Drug Administration (FDA) has cleared...
Medivis SurgicalAR Gets FDA Clearance
Technology | Virtual and Augmented Reality | June 10, 2019
Medivis announced that its augmented reality (AR) technology platform for surgical applications, SurgicalAR, has...
Glassbeam Announces New Clinsights Application Suite for Healthcare Provider Market
Technology | Analytics Software | June 10, 2019
Glassbeam launched Clinsights, a new revitalized application suite powered by artificial intelligence/machine learning...
The DeepAAA algorithm, developed at the MGH & BWH Center for Clinical Data Science, accurately detected and measured an abdominal aortic aneurysm (AAA) in a CT image even though appearance of the AAA was complicated by a blood clot

The DeepAAA algorithm, developed at the MGH & BWH Center for Clinical Data Science, accurately detected and measured an abdominal aortic aneurysm (AAA) in a CT image even though appearance of the AAA was complicated by a blood clot. (The algorithm drew a green circle around the aneurysm.) Image courtesy of Varun Buch, MGH & BWH Center for Clinical Data Science

Feature | Artificial Intelligence | June 10, 2019 | By Greg Freiherr
Editor’s note: This article is the second in a content series by Greg Freiherr covering the ...
Volpara Health Technologies to Acquire MRS Systems Inc.
News | Mammography Reporting Software | June 04, 2019
Volpara Health Technologies, Volpara Solutions' parent company, has signed a binding agreement to acquire U.S.-based...
SIIM and ACR Host Machine Learning Challenge for Pneumothorax Detection and Localization
News | Artificial Intelligence | June 03, 2019
The Society for Imaging Informatics in Medicine (SIIM) and the American College of Radiology (ACR) are collaborating...
Artificial Intelligence In It For Long-Haul, Says Radiology Leader
Podcast | Artificial Intelligence | June 03, 2019
Artificial Intelligence In It For Long-Haul, Says Radiology Leader